Night Detection of Parked Vehicles

ABSTRACT

To detect parked vehicles at night, the present invention discloses night-detection device and method. The night-detection device comprises a moving-vehicle sensor and a parked-vehicle sensor. It uses the light beam from a passing-by vehicle to detect parked vehicles.

BACKGROUND

1. Technical Field of the Invention

The present invention relates to the field of electronics, and more particularly to device and method to detect parked vehicles at night.

2. Prior Arts

Locating a vacant parking space causes much frustration to motorists. It increases fuel consumption and has a negative impact to the environment. To conserve energy resources and enhance the quality of the environment, it is highly desired to develop a parking-monitoring system, which can transmit substantially real-time parking states (i.e. occupied or vacant) to motorists. Based on the parking states, a motorist can be guided towards a vacant parking space at destination.

Parking enforcement is an important aspect of city management. The current parking-enforcement system is patrol-based, i.e. parking enforcement officers patrol the streets and/or parking lots to enforce the parking regulations. This operation requires significant amount of man power and also consumes a lot of fuel. It is highly desired to take advantage of the above-mentioned parking-monitoring system and automatically measure the parking time for each monitored parking space.

Both parking monitoring and enforcement are based on parked vehicle detection. Parked vehicle detection preferably can be carried out both during the day and at night. This is particularly important for commercial districts during the day and for residential areas at night. Relying on the natural light to capture the images of a parking area, prior arts only work during the day. At night, because street lights generally do not provide adequate lighting coverage (often blocked by trees or other obstacles), prior arts cannot reliably detect parked vehicles.

Objects and Advantages

It is a principle object of the present invention to conserve energy resources and enhance the quality of the environment.

It is a further object of the present invention to reliably detect parked vehicles at night.

It is a further object of the present invention to provide parking monitoring at night.

It is a further object of the present invention to provide parking enforcement at night.

In accordance with these and other objects of the present invention, the present invention discloses device and method to detect parked vehicles at night.

SUMMARY OF THE INVENTION

The present invention discloses a night-detection device for parked vehicles. It uses the light beam from a passing-by vehicle to detect parked vehicles. The night-detection device comprises a parked-vehicle sensor for monitoring a parking area and a moving-vehicle sensor for sensing a moving vehicle around the parking area. The parked-vehicle sensor captures the images of the parking area when the moving-vehicle sensor detects a passing-by vehicle. These images are then processed to determine the state of each parking space in the parking area.

Because it has a limited range (with effective range of ˜20 meters), the light beam of the passing-by vehicle can only illuminate a small number of the parked vehicles (typically around three vehicles). Considering that the passing-by vehicle can only illuminate the parking area for a few seconds, the parked-vehicle sensor needs to capture at least one image every two seconds. This is more frequent than that during the day when the parked-vehicle sensor only needs to capture an image every five to ten seconds. Accordingly, for a parked-vehicle sensor with a powerful processor, the images can be processed in real time; for a parked-vehicle sensor with a less powerful processor, the images can be recorded first and then processed after the moving vehicle is out of range.

Because the parked vehicles are illuminated by the light beam of a passing-by vehicle, not by the natural light, image processing at night is different from that during the day. First of all, the region of interest (ROI) at night is different from that during the day. The ROI's at night have different shapes and locations than those during the day. Secondly, the extracted features at night are different from those during the day. The extracted features at night are reflections (where the pixel intensity is large), whereas the extracted features during the day are edges (where the pixel intensity changes sharply). For inline parked vehicles (i.e. vehicles parked along a line and the parked-vehicle sensor captures the side image of the parked vehicles), typical extracted features at night include the tail-light reflection, the wheel reflection and the body reflection. For side-by-side parked vehicles (i.e. vehicles parked side-by-side and the parked-vehicle sensor captures the tail/head image of the parked vehicles), typical extracted features at night include the rear/front bumper reflection and the tail/head-light reflection (“/” means “or” here).

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a top view of a street with vehicles parked along its side and a moving vehicle passing by these parked vehicles;

FIG. 2 is a block diagram of a preferred night-detection device for parked vehicles;

FIG. 3 is a block diagram of a preferred parked-vehicle sensor;

FIGS. 4A-4C disclose several preferred moving-vehicle sensors and moving-vehicle detection methods;

FIGS. 5A-5B are flow charts showing two preferred night-detection methods for parked vehicles;

FIG. 6 illustrates the detected features on a parked vehicle during the day (prior art);

FIG. 7 illustrates the detected features on a parked vehicle at night;

FIGS. 8A-8C are real images of detected features on various parked vehicles at night.

It should be noted that all the drawings are schematic and not drawn to scale. Relative dimensions and proportions of parts of the device structures in the figures have been shown exaggerated or reduced in size for the sake of clarity and convenience in the drawings. The same reference symbols are generally used to refer to corresponding or similar features in the different embodiments.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Those of ordinary skills in the art will realize that the following description of the present invention is illustrative only and is not intended to be in any way limiting. Other embodiments of the invention will readily suggest themselves to such skilled persons from an examination of the within disclosure.

Referring now to FIG. 1, a street 20 with several parked vehicles and a passing-by vehicle is shown. The street 20 is along the x-axis and has two curbs 20 a, 20 b. Along the curb 20 a, there are a number of parking spaces (e.g. 10 a-10 f . . . ). On the opposite curb 20 b, a parking-monitoring device 30 a is installed to monitor a large parking area 35, which includes the parking spaces 10 a-10 f. Generally, the device 30 a is mounted on a support such as a utility pole or a street-lamp post, which also provides power to the device 30 a. To make it easier to detect a parked vehicle, the device 30 a is preferably mounted at a position higher than the highest roof of the parked vehicles.

Within the monitored parking area 35, four parking spaces 10 a, 10 c, 10 d and 10 f are occupied by the vehicles 40 a, 40 c, 40 d and 40 f, respectively, while the other two parking spaces 10 b, 10 e are vacant. During the day (i.e. under the natural lighting), the states of these parking spaces 10 a-10 f can be easily monitored by the parking-monitoring device 30 a. At night, because these parked vehicles may not have enough lighting for the parking-monitoring device 30 a to make reliable detection, the light beam 60 from a moving vehicle 50, which illuminates the parked vehicles while passing by, is used to determine the states of the parking spaces 10 a-10 f.

Referring now to FIG. 2, a preferred night-detection device 30 for parked vehicles is disclosed. This night-detection device 30 is actually the parking-monitoring device 30 a. It takes advantage of the light beam 60 from a moving vehicle 50 which illuminates the parked vehicles while passing by. The night-detection device 30 comprises a parked-vehicle sensor 80 for monitoring a parking area and a moving-vehicle sensor 70 for sensing a moving vehicle around this parking area. The parked-vehicle sensor 80 captures the images of the parking area 35 when the moving-vehicle sensor 70 detects a passing-by vehicle 50. A passing-by vehicle 50 is a moving vehicle within a pre-determined range from the parked area 35. More details on the parked-vehicle sensor 80 and the moving-vehicle sensor 70 are disclosed in FIG. 3 and FIGS. 4A-4C, respectively.

FIG. 3 is a block diagram of a preferred parked-vehicle sensor 80. It comprises an optical detector 82, a processor 84 and a memory 86. The optical detector 82 captures the images of the monitored parking area 35 and it is generally a camera. It may also comprise a number of cameras facing different directions. The processor 84 processes the images captured by the optical detector 82 to determine the parking states. It could be any type of central-processing unit (CPU) and/or digital signal processor (DSP). The memory 86 could be any type of non-volatile memory (NVM), e.g. flash memory. It stores at least a portion of the images captured by the optical detector 82. It also stores an operating system for the parking-monitoring device 80. Preferably, the operating system is an operating system of a smart-phone, e.g. iOS or Android. It further stores at least a parked vehicle detection algorithm 87. This algorithm 87 configures the processor 84 to detect parked vehicles.

FIGS. 4A-4C disclose three preferred moving-vehicle sensors 70 and moving-vehicle detection methods. In the preferred embodiment of FIG. 4A, the moving-vehicle sensor 70 could be an audio sensor, an optical sensor, or an electromagnetic sensor. The audio sensor listens to the ambient sound change caused by a nearby moving vehicle 50; the optical sensor monitors the ambient light change caused by a nearby moving vehicle 50 (more details disclosed in FIG. 4B); the electromagnetic sensor detects the changes in electromagnetic wave caused by a nearby moving vehicle 50.

FIG. 4B discloses another preferred moving-vehicle sensor 70. It uses the parked-vehicle sensor 80 of FIG. 3 as the moving-vehicle sensor 70. Note that the memory 86 of the parked-vehicle sensor 80 further stores a moving vehicle detection algorithm 89. This algorithm 89 configures the processor 84 to detect an incoming light beam on the street. Once the intensity of this light beam is above a threshold, the moving vehicle is considered in range.

FIG. 4C discloses a third preferred moving-vehicle sensor. For the parked-vehicle sensor 80 a monitoring a parking area in the block 22 a, the moving-vehicle sensor 70 b in an adjacent block 22 b are used to provide an advance notice of a passing-by vehicle 50. The moving-vehicle sensor 70 b can communicate this advance notice to the parked-vehicle sensor 80 a using a wireless means 98, e.g. WiFi or Bluetooth. Note that the parked-vehicle sensor 80 a and the moving-vehicle sensor 70 b could be a potion of the parking-monitoring device of their respective block. With the advanced notice, the parked-vehicle sensor 80 a can monitor the parked vehicles more efficiently and more accurately.

Referring now to FIGS. 5A-5B, flow charts showing two preferred night-detection methods for parked vehicles are shown. In the preferred method of FIG. 5A, the captured images are processed in real time as the moving vehicle 50 is passing the parking area 35. On the other hand, in the preferred method of FIG. 5B, the captured images are processed after the moving vehicle 50 has left the monitored parking area 35.

As is disclosed in FIG. 5A, the first preferred night-detection method includes the following steps. The moving-vehicle sensor 70 senses a moving vehicle 50 (step 110). If the moving vehicle is in range (step 120), the parked-vehicle sensor 80 captures an image of the parking area 35 (step 130). This image is processed for each parking space, particularly for the parking spaces which are illuminated by the light beam 60 of the passing-by vehicle 50 (step 140). Repeat these steps 130, 140 until the moving vehicle 50 is out of range (step 150). Then wait for another moving vehicle (step 160).

Because it has a limited range (with effective range of ˜20 meters), the light beam 60 of a passing-by vehicle 50 can only illuminate a small number of the parked vehicles (typically around three vehicles). Considering that the passing-by vehicle 50 can only illuminate the parking area for a few seconds, the parked-vehicle sensor 80 needs to capture at least one image of the parking area 35 every two seconds. This is more frequent than during the day when the parked-vehicle sensor 80 only needs to capture an image every five to ten seconds. Accordingly, for a parked-vehicle sensor 80 with a powerful processor 84, the images can be processed in real time; for a parked-vehicle sensor 80 with a less powerful processor 84, the images can be recorded first and then processed after the moving vehicle 50 is out of range. This is further illustrated in FIG. 5B. When the moving vehicle 50 is in range (step 120), the parked-vehicle sensor 80 only captures the images (step 130) and records them to the memory 86 (step 145), but does not process these images. After the moving vehicle 50 is out of range (step 150), the processor 84 processes these images and determines the states of the parking area 35 (step 155).

Because the parked vehicles are illuminated by the light beam 60 of a passing-by vehicle 50, not by the natural light, image processing at night is different from that during the day. FIGS. 6 and 7 compare these differences, primarily in the areas of region of interest (ROI) and signature features. Here, a ROI is a region in an image that is image-processed to detect if a vehicle is parked in an associated parking space; and a signature feature is a feature on a vehicle indicating that this vehicle is parked in a parking space of interest.

FIG. 6 shows the ROI's 200 a, 200 c for the vehicles 40 a, 40 c parked in the parking spaces 10 a, 10 c along the curb 20 a during the day. Each ROI (e.g. 200 a) roughly starts from a side lines (e.g. “ab”) of the parking space (e.g. 10 a) and extends upward to cover at least a side window of the vehicle (e.g. 40 a). The extracted features in the ROI are signature edges of the vehicle. For an inline parked vehicle, its signature edges include the bottom edge of its body and the bottom edge of its side window. More details on the day detection of parked vehicles are disclosed in U.S. patent application “Occluded Vehicle Detection”, App. Ser. No. 61/883,122, filed Sep. 26, 2013.

FIG. 7 shows the ROI's for the vehicles 40 a, 40 c at night. Each vehicle (e.g. 40 a) has two ROI's (e.g. 210 a, 220 a). The first ROI 210 a covers at least a wheel and a portion of the body of the vehicle 40 a, while the second ROI 220 a covers the tail-light of the vehicle 40 a. The extracted features at night are different from those during the day: the extracted features at night are reflections (where the pixel intensity is large), whereas the extracted features during the day are edges (where the pixel intensity changes sharply). For an inline parked vehicle, its signature edges include the wheel reflection 320, the tail-light reflection 330 and the body reflection 340. Here, a signature reflection can be detected by searching for the pixels whose intensity is larger than a threshold within the ROI.

FIGS. 8A-8C illustrate the detected features on various parked vehicles at night. These figures use the real-world photos. In FIG. 8A, the signature features of an inline parked vehicle 40 g with its tail facing the camera include the wheel reflection 320 and the tail-light reflection 330. In FIG. 8B, the signature features of an inline parked vehicle 40 h with its head facing the camera include the wheel reflection 320 and the body reflection 340. In FIG. 8C, the signature features of a side-by-side parked vehicle 40 i include the tail-light reflection 340 and the rear bumper reflection 350. Note that this vehicle 40 i is parked head-in-first. For a vehicle parked tail-in-first, its signature features include the head-light reflection and the front bumper reflection.

While illustrative embodiments have been shown and described, it would be apparent to those skilled in the art that may more modifications than that have been mentioned above are possible without departing from the inventive concepts set forth therein. The invention, therefore, is not to be limited except in the spirit of the appended claims. 

1-20. (canceled)
 21. A night-detection device for parked vehicles, comprising: a parked-vehicle sensor for determining whether a parking space in a parking area is occupied by a parked vehicle; and a moving-vehicle sensor for sensing a moving vehicle within a pre-determined range of said parking area; wherein said parked-vehicle sensor captures at least an image of said parking area when said moving-vehicle sensor detects said moving vehicle.
 22. The system according to claim 21, wherein said moving-vehicle sensor is an audio sensor, an optical sensor, or an electromagnetic sensor.
 23. The system according to claim 21, wherein said moving-vehicle sensor is located at the same location as said parked-vehicle sensor.
 24. The system according to claim 21, wherein said moving-vehicle sensor is located at a different location from said parked-vehicle sensor.
 25. The system according to claim 24, wherein said moving-vehicle sensor communicates with said parked-vehicle sensor using a wireless means.
 26. The system according to claim 21, wherein said parked-vehicle sensor comprises an optical detector, a processor and a memory.
 27. The system according to claim 26, wherein said optical detector comprises at least a camera.
 28. The system according to claim 27, wherein said camera captures images of said parking area more frequently at night than during the day.
 29. The system according to claim 26, wherein said memory stores a parked vehicle detection algorithm.
 30. The system according to claim 26, wherein said memory stores a passing-by vehicle detection algorithm. 